The Massive Redeployment Hypothesis

Description: The massive redeployment hypothesis (MRH) is a theory about the functional organization of the human cortex, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components—originally developed to serve some specific purpose—were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs.

MRH suggests that in order to determine the functional role of a given brain area it is necessary to consider its participation across multiple task categories, and not just focus on one, as has been the typical practice. Among other illustrations of the fruitfulness of this approach is some preliminary work on understanding the functional role of left angular gyrus in both math cognition and finger gnosia.

Researchers: M. L. Anderson, M. Penner-Wilger

Representative Publications: "Neural reuse: A fundamental organizational principle of the brain","Neural reuse in the evolution and development of the brain: Evidence for developmental homology?", "The massive redeployment hypothesis and the functional topography of the brain", "Evolution of cognitive function via redeployment of brain areas", "Massive redeployment, exaptation, and the functional integration of cognitive operations", "An alternative view of the relation between finger gnosis and math ability: Redeployment of finger representations for the representation of number", "On the grounds of x-grounded cognition", "Circuit sharing and the implementation of intelligent systems"

Neuro-Image based Co-Activation Matrix (NICAM) database project

Description: This project involves compiling large numbers of brain imaging (primarily fMRI) studies and applying some simple data mining and graph theory based analytical techniques to investigate functional cooperation between brain regions. Applications of the project include understanding the basic functional structure of the cortex, and relating fMRI to EEG data to support such medical applications as epileptic seizure prediction. A special project website can be found here.

Researchers: M. L. Anderson, A. Chaovalitwongse

Representative Publications: "Investigating functional cooperation in the human cortex with graph-theoretic methods", "Brain network analysis of seizure evolution"

Description:  Embodied Cognition is an approach to understanding the mind that treats cognition as a coordinated set of tools evolved by organisms for coping with their environments. This approach foregrounds agency and environmental interaction over internal symbol manipulation (although it need not deny the importance of the latter). To find out what embodied cognition has to do with AI, see a canned history of AI.

Researchers: M. L. Anderson

Representative Publications:,  "Eroding the boundaries of cognition: Implications for embodiment"   “Embodied cognition: A field guide” and “How to study the mind: An introduction to embodied cognition",  "On the grounds of x-grounded cognition" 

Description: An investigation of the thesis that metacognitive monitoring and control (in a form we call the metacognitive loop, or MCL) can play an important role in improving the perturbation tolerance of real-world agents, that is, their ability to detect and recover from errors or unexpected changes. We have shown that adding an MCL component can improve the performance of a diverse range of systems from natural-language human-computer interfaces to simple Q-learners. A more specialized project along these same lines is an investigation into the use of metalanguage in conversation, and its role in helping maintain the fluidity, flexibility and error-tolerance of human-human dialog. 

Researchers: M. L. Anderson, T. Oates, D. Perlis

Representative Publications: " "The Metacognitive Loop and Reasoning about Anomalies", , "A self-help guide for autonomous systems", "The metacognitive loop I: Enhancing reinforcement learning with metacognitive monitoring and control for improved perturbation tolerance" (preprint, published version), "Active logic semantics for a single agent in a static world", "An Approach to Human-Level Commonsense Reasoning", "A self-help guide for autonomous systems"